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- 1Actor-critic reinforcement learning algorithms
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Author: Ghavamzadeh, Mohammad
Author: Lee, Mark
Subject: Actor-critic reinforcement learning algorithms
Subject: Approximate dynamic programming
Subject: Bootstrapping
Subject: Policy gradient methods
Collections: Computing Science, Department of
Collections: Computing Science, Department of/Technical Reports (Computing Science)
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2009
Bhatnagar, Shalabh, Sutton, Richard, Ghavamzadeh, Mohammad, Lee, Mark
Technical report TR09-10. We present four new reinforcement learning algorithms based on actor-critic, function approximation, and natural gradient ideas, and we provide their convergence proofs. Actor-critic reinforcement learning methods are online approximations to policy iteration in which...
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